Upload app.py

app.py

@@ -10,7 +10,13 @@ from glycowork.glycan_data.loader import lib
 
 
 def fn(model, class_list):
-  def f(glycan):
+  def f(glycan, model):
+    if model == "No data augmentation":
+      model = torch.load("model1.pt")
+      model.eval()
+    else:
+      model = torch.load("mode2.pt")
+      model.eval()
     glycan = [glycan]
     label = [0]
     data = next(iter(dataset_to_dataloader(glycan, label, batch_size=1)))
@@ -30,8 +36,6 @@ def fn(model, class_list):
     return pred
   return f
 
-model = torch.load("model.pt")
-model.eval()  
 class_list=['Amoebozoa', 'Animalia', 'Bacteria', 'Bamfordvirae', 'Chromista', 'Euryarchaeota', 'Excavata', 'Fungi', 'Heunggongvirae', 
             'Orthornavirae', 'Pararnavirae', 'Plantae', 'Proteoarchaeota', 'Protista', 'Riboviria']
 
@@ -39,12 +43,11 @@ f = fn(model, class_list)
 
 demo = gr.Interface(
     fn=f,
-    inputs=[gr.Textbox(label="Glycan sequence")],
-    outputs=[gr.Label(num_top_classes=15, label="Class prediction")],
+    inputs=[gr.Textbox(label="Glycan sequence"), gr.Radio(label="Model",choices=["No data augmentation", "Random node deletion"])],
+    outputs=[gr.Label(num_top_classes=15, label="Prediction")],
     allow_flagging=False,
     title="SweetNet demo",
-    examples=["GlcOSN(a1-4)GlcA(b1-4)GlcOSN(a1-4)GlcAOS(b1-4)GlcOSN(a1-4)GlcOSN",
-    "Man(a1-2)Man(a1-3)[Man(a1-3)Man(a1-6)]Man(b1-4)GlcNAc(b1-4)GlcNAc",
-    "Neu5Ac(a2-3)Gal(b1-3)[Neu5Ac(a2-6)]GlcNAc(b1-3)Gal(b1-4)Glc-ol"]
+    examples=[["GlcOSN(a1-4)GlcA(b1-4)GlcOSN(a1-4)GlcAOS(b1-4)GlcOSN(a1-4)GlcOSN", "No data augmentation"],
+    ["Man(a1-2)Man(a1-3)[Man(a1-3)Man(a1-6)]Man(b1-4)GlcNAc(b1-4)GlcNAc", "Random node deletion"]]
 )
 demo.launch(debug=True)